CDO Matters Ep. 14 | MVP Data Strategy for CDOs

December 30, 2022

Episode Overview:

First impressions are everything.

As a brand-new CDO, it is important to hit the ground running with a data strategy that pinpoints key use cases and quickly delivers value within an organization.

In our 14th episode, Malcolm shares his perspectives on the top deliverable for most CDOs: the definition and execution of a corporate data strategy. He outlines his model for a ‘Data Strategy Minimum Viable Product’ (MVP), which embraces a highly iterative and pragmatic approach to defining and executing a strategy. This approach starkly contrasts more traditional approaches which often take years to deliver any business value.

Rather than separating a strategy’s definition from its execution, the Data Strategy MVP deeply interconnects the execution with the ongoing evolution of the data strategy — where CDOs can earn the right to change corporate cultures or operating models by delivering business value rather than management edict. 

Malcolm argues that forcing a business to wait years — or even several months before it will realize any benefits of a data strategy — is a key reason for shortened CDO tenures. 

While a typical approach to a data strategy would involve 6-12 months of business analyses and requirements gathered across an entire enterprise before actually executing a strategy, the Data Strategy MVP hinges on a razor-sharp focus on quickly identifying a few key business outcomes.

This is quickly followed by the definition and execution of a data strategy specifically to address those limited sets of outcomes. By repeatedly focusing on a small set of outcomes, organizations can successfully execute a holistic data strategy.  

Malcolm also dives into how taking a more tactical and results-driven approach to implementing a data strategy requires a strong data leader who can balance longer-term needs — such as defining an adaptable technology architecture or the right governance model — against short-term needs.

Finding this balance will not be easy but is necessary to ensure short-term decisions do not compromise the ability to fully align the data to the business strategy in the long haul.  

Another key to the Data Strategy MVP — as outlined in the shared model — is the acknowledgment of the several business characteristics that CDOs cannot change in the short term. These include the data culture, corporate operating models and overall data and analytics maturity level.

While more traditional strategy approaches would place changes to these things as strategic dependencies, Malcolm instead argues they should be considered more as constraints. This helps guide decisions on the best business outcomes the evolving strategy should be focused on in the immediate future.  

CDOs who have been tasked to execute a data strategy should find this episode of CDO Matters highly useful — especially those concerned that too much of a focus on data strategy is hampering their ability to deliver value.

Newer CDOs unfamiliar with more agile approaches to program management will also benefit from this episode — as will those aspiring CDOs who are looking to make an impact for their business partners by finding ways to bring value in more iterative ways.  

Key Moments

  • [2:10] Why Are CDO Tenures So Short-lived?
  • [4:12] The Responsibilities of the Modern CDO when Establishing a Data Strategy
  • [7:02] Creating a Centralized Data Culture
  • [13:05] MVP Data Strategy Attributes
  • [18:45] Defining Your Outcomes
  • [20:52] Filling Gaps in Governance Maturity
  • [24:30] Leveraging Analytical Insights Rather Than Operational
  • [28:15] Delivering Realistic Business Outcomes
  • [30:40] Succeeding as a CDO
  • [33:05] Establishing an Analysis Roadmap and Governance Framework
  • [36:46] Placing Technology at the End of Your Strategy
  • [42:10] Summarizing How to Provide Significant Value

Key Takeaways

Why are CDO Tenures so Short-lived? (10:32)

“I would argue that one of the reasons for very, very, short CDO tenures is that [CDOs] rightfully identify that some fundamental ways the business operates need to change… however when you put those organizational changes or those cultural changes or those operating model changes as dependencies to be able to deliver value — and if you make those changes your top priority — you are going to have a hard time delivering value in the short term.” — Malcolm Hawker

Start Small and Grow from There (18:32)

“A key to this whole thing — being MVP-driven — is to focus on a limited number of outcomes… not all of them — one or two. If you want to take an MVP approach to a strategy — and I would argue it’s the best thing you can do is to show some quick wins and show some value and not get stuck in an 18-month long discovery and consulting engagement.” — Malcolm Hawker

Delivering Plausible Value (32:25)

“If you want to succeed at a data strategy…you do need to incorporate some idea of executing against the strategy as a part of your strategic model, where you plan to deliver iteratively as a part of executing on that strategy. Where that strategy evolves based on your ability to deliver.” — Malcolm Hawker 

Limit Your Scope and Don’t Boil the Ocean (36:14)

“For now, you just need to figure out the governance needed to enable [your top outcome]. It’s simple, stay focused, keep a limited scope, be agile, deliver on one outcome. Figure out the governance dependencies for that one outcome instead of figuring out the governance dependencies for everything. Because if you try to figure out the governance dependencies for everything, you’ll be at it every day for the next three years — two to three years easily. That will consume every resource you’ve got, you won’t have delivered value, and it’s not going to be good. It’s not.” — Malcolm Hawker

Episode Links & Resources:

Episode Transcript:

Malcolm Hawker 

Hi, I’m Malcolm Hawker, and this is the CDO Matters podcast. The show where I dig deep into the strategic insights, best practices and practical recommendations that modern data leaders need to help their organizations become truly data-driven. TuneIn for thought provoking discussions with data. IT and business leaders to learn about the CDO matters that are top of mind for today’s chief data officers. This is Malcolm Hawker I’m your host of the CDO Matters Podcast. This is our 14th episode of CDO CDO Matters. It’s it’s. It’s amazing to think we just started a few months ago and and we’re already at our 14th episode. Time certainly does fly. We are now here entering the last few days of 2022. Been an interesting year to say the least. I’m going to spare you one of the, you know, kind of the year in summary, type podcasts or things that you see online this time of year. I am going to talk more about data strategy today and interestingly. I’m not going to have a guest. I’m going to be the guest. We’re trying something a little bit new here and tapping my wealth of knowledge that I gained while as a quarter analyst and and having run and implemented MDM programs and data governance programs and been a vendor consultant, analyst, buyer, you name it. I’ve got a. Number of years. Of under my belt here of of knowing what works and what doesn’t work so. We’re going to. Just go with me as the guest today. This podcast is. Really, a result of a post that I’ve made on LinkedIn a little while ago in reaction to some ongoing dialogue related to Chief Data Officer tenures. And I had noted some recent research that said that CEO tenures were. Relatively short to maybe. 2 1/2 years and by comparison to CIO’s, there were half of that, so the average CIO tenure was up upwards above 4 years, pushing to five years. And that’s really what led to this conversation. Today I wanted to dive in to try to understand. OK, well. Why is that? And there’s a. Number of reasons why CDO tenures are short. One of them is. It’s a relatively new role. I think that one’s an easy one to explain relatively new role and a. Lot of leadership. Teams and a lot of companies are just kind of coming to terms. For the first time with with what does this mean? What are the roles and responsibilities what? Are the expectations of of achieved data? Sir, and I think they most certainly. Are some growing pains there. There are other reasons for short 10 years. I think the biggest one is beyond this, just kind of being growing pains and the biggest one is I’ll be honest here and say a failure to deliver value at least a failure to deliver value in a relatively quick amount of time. That’s really what? Going to be talking about today you notice. On the. Thumbnail today’s topic is the MVP minimum viable? Product of a data strategy. If you ask me why CDO tenures are short? Yes, as a new role. Yes, they’re struggling to deliver value. Yes, they’re struggling to connect investments in data and analytics and the delivery of business outcomes that will be that’s. A separate podcast. So, so the inability to deliver tangible business value. In the form of measurable KPIs, huge issues for for CDO’s and is an ongoing topic of this podcast. Ongoing topic of the things that I put on LinkedIn and on and on. We’re not going. To focus on there today. What we’re going to focus on more is the strategy aspects. So job number one of the Chief data officer is to define a data strategy for an organization. When I was a Gartner. Analyst talking to over 1500. CIO’s and CEO’s day in and day. Out one of the one common. Theme really emerged in relation to data strategy. And a common. Theme was was the data strategy was put as. This this long pole. This dependency of something that I need to do. First, before I can really start to to to to make inroads from kind of from an execution or an implementation perspective. So I would see often CEO’s would would come into their role and they say OK job number one on day one is. To define my data strategy. And that took a reasonable amount of time. For any, any any any any sizable company at all. I mean you’re talking about about a lot of different things to consider here in terms of of of the data. And often what I Saw was that as CBS would embark on. This data strategy. They would rightfully. Be looking at things like your data and analytics, governance, maturity, right? You’d rightfully be looking at things like the overall operating model. You’d rightfully be looking at things like the corporate culture, right, and. CEO’s would go about. Defining these strategies and would talk to senior business leaders. Talk to fellow members of the C-Suite, talk to the CIO, talk to others and say OK, what? What do you want? To have happen here and. CDO’s would learn well. We want to do a B&C. These are the key outcomes that we want to drive. We want to digitally transform. We want to revolutionize our customer experience. We want to optimize our supply chain. Whatever those high level outcomes are, CEO’s would relatively quickly. Figure these things out. But as a part of doing kind. Of their discovery. About the the the, the landscape and the culture and the operating model and and the existing competencies of the team. What a lot of CEO’s would soon. Discover is that there were gaps between. Being where they needed to be from a culture perspective from an operating model perspective, from a competency perspective and those gaps would exist and the CEO would say OK, I need to close those gaps. In order to successfully deliver on the expected business outcomes of that we’ve been talking about for. The last few weeks. And it was. Those things those dependencies, those gaps, right? Whether we’re talking about culture, whether we’re talking about operating model, whether we’re talking about governance or maturity, or competency levels or or or. On and on. These gaps would be kind of positioned as hard dependencies in order to get anything done or hard dependencies in order to fulfill on those key outcomes that that were identified as, as must have priorities. So what this led to often was CEO’s thinking that they had to change the corporate culture of an organization before they could make. Any really big inroads, right? I would hear. All the time. 

Malcolm Hawker 

CDO would be brought in. I vividly recall one conversation that I had with the CEO of a of a large consumer packaged good globally operating Consumer Packaged Goods company who who said, well, you know, we we need to optimize our supply chain and we need to revolution our customize revolutionize our customer experience. Those are kind of two key things that we’re trying tied to a digital transformation. And in order to get the visibility that that CDO needed to do all of that in order to get access to the data that the CDO needed to do that, the CDO kind of acknowledged that, hey. We’ve got a bunch of fiefdoms. Within our operating model, we’ve got the. You know, the Brazilian business and we’ve got the Canadian business and we’ve got all of these business. Not only are we operating at A at a country specific level, but we’re operating at it from a divisional level, so we’ve got individual divisions within each of these companies. And and you know what? These companies don’t like to share data. These different divisions don’t even really kind of. Like to share data. We’ve got a highly, highly, highly decentralized operating model and I need to fix that in order to deliver on my mandate. And I would be called up as a Gartner analyst to say, OK. Well, how do I fix that? How do I make this company become? Slightly more centralized. It’s a great example. How do we become slightly more centralized from a data management perspective? Because in order. To deliver on this mandate that I’ve got from a strategy perspective, that’s what we need to do. We need to take. Kind of a more centralized, maybe a little bit more of a top down approach. Just managing some of the data and some of the business processes maybe. Not all of them, but maybe some of them. I would ask. OK? Well first of all, do do you have the kind of the firepower behind you, right? Do you have the support of the CEO? Even to do that right? And often the answer was whether it was this one use case that I’m talking about or others this. This is a common theme by the. Way is that. I need to change the operating model of the business somehow. Some way in. Order to be successful as a CEO. I’d say, OK, well, do you have the fire power behind you to do that? Do you have the air cover of the CEO to do that? And and often the the the question the answer. Was yeah I. I think so. But I’ve gone and talked to the divisional leaders and they don’t think that they have that mandate. So this is another way of saying is that that CDO was walking in basically to a lion’s den, and as much as changing that operating model and and not only is this an operating model, but this is very much a culture as well. These things, these things from the perspective of centralized business process management versus decentralized business process management operating. Model and culture. They are hard wired together so. To try to change that, you’re talking years and years and years, right? Especially for a very very big company. But the world that we. 

Malcolm Hawker 

Live in now is a world of you’ve got six months to deliver something here, right? This is a. World of digital transformation. This is a world of digital acceleration. This is a world of constant change and disruption. Whether that is global pandemics or supply chain interruptions or changing customer. Eats right. Or maybe that’s some new startup that is trying to disrupt your business. It it doesn’t matter, we live in a world where asking your organization for three or four years in order to deliver value as a CEO isn’t really really tall order, so I would argue that one of the reasons for very, very short CDO tenures is that. They rightfully identify that some fundamental things about the way that the business operates needs to change and and that’s and that’s generally accurate, right? And and those things do absolutely positively need to change in the longer run. However, when you put those organizational changes, those culture changes. The operating model changes as dependencies. To be able to deliver value, and if you make those changes, your top. Party you’re going to have a hard, hard hard time delivering value in the short term and a year will go by and your CEO will be asking. OK, what? What did our new CEO deliver? Well, we’ve hired some very, very expensive consultants. We may have a high level road map. We may. Have some other discovery. And we may know where some of the data lives. Maybe we’ve even built some data catalogs and some other some other kind of interesting anecdotal insights based on the purchase of a. Lot of tech, right? Like a data catalog. Or other governance tools and that kind. Of thing, but in terms of the business. 


Are you? 

Malcolm Hawker 

The things that the business. Really cares about where are we? Well that CDO could step back and. Say, well, you know. I I couldn’t do that because you gave me. A mandate to. Become more centralized from a business process management perspective. Or you gave me a mandate of of of changing the way that marketing operates, or you’ve given me a mandate in essence of changing. The way that. Procurement operates and I’m doing my best to execute. Those changes. But I’m running into friction and I’m running. I’m running into pushback from those divisional departments. And yes, you may have given me the mandate, and you may have said that this is important and I and and you said that I had the air cover, but when I went to go talk to those people, they don’t want to change or they feel that they don’t have the edict to change or they feel like changing will negatively impact. Their ability to deliver outcomes for the business. And I’m trying to change all of those things and I’m trying to change the operating model because that’s what’s required to deliver on the outcomes that you told me are important, but I’m having a hard time doing it and that’s why I haven’t delivered anything in the last 12 to 18 months. Which negative or which? Which ultimately will probably lead to some sort of reevaluation of the of. The program as a whole, so. As a result of that, what I want to share with you. Today, not that button. Uh, what I want to share with you today. Is is something I’m I’m calling the the data strategy MVP right? If there was one, there isn’t one. There’s there’s a lot of things that I would recommend to to to new. CEO’s but From the perspective of data strategy, which is almost always job number one for a new CDO, go and define a data set. If there was 11 little kind of bit of advice that I could give to you, it would be to try to be as agile capital A as agile as possible. When it comes to defining a. Data strategy right so? When looking at this model and again, my apologies if you are on the. If you’re on the audio only channels here, I’ll try to describe the this model, which is available at which I posted on. LinkedIn a couple of times already, so this this model. Here is what I’m calling the the MVP data strategy and it really kind of has two different kind of circles right spinning wheels as as it were. There’s one circle on the outside that that talks about the what I would call largely our our kind of your constraint. Right, right where I would argue things like if your overall business strategy right, your overall culture and operating model and your data and analytics, governance, maturity. These things are not going to change in the short run. You’re going to need years. To change these things that are on this outer ring of this model. Right, so do you need to know what your data and analytics governance maturity is? Yes, do you need to know what your culture and operating model is? Of course you do. But I would argue if you start with step #1, defining kind of your overall desired key outcomes where those outcomes would obviously want to foot and tie back to your overall business strategy so you know an alignment between data strategy, high level outcomes of a data strategy and the business strategy have those things in the mind. Force, but then go about understanding. What your culture and operating? Model is what your some. Of your kind. Of your roadblocks are going to be right. You could you could. Identify that you want a a overall outcome of. Let’s just say let’s let’s let’s let’s let’s. Re architect or reengineer our, for example, our supplier onboarding process. If you wanted to optimize your relationship with your suppliers, you could want better supplier management or or or or or better procurement processes, or. And more exceptional. Customer experience, maybe that’s a better example. Customer experience because everybody’s focused. Most are focused on supply but as well, but only when you’re making stuff. So everybody’s got customers. Let’s focus on customer let’s. Let’s say that you could have a a desired outcome here of you want to significantly enhance the customer experience, maybe right now you’ve kind of got low Net Promoter scores, or you’ve got challenges related to. Your tension or cost of acquisition is high, and you want to improve your customer experience with the ultimate goal of the group. Improve your customer retention. Let’s say that that is kind of a high level outcome that you want. You can quickly identify that we’re not talking about weeks and months to figure. That stuff out. Probably something that was included. A topic that was being discussed during your recruitment. I I would have to imagine we we we are seeking a CDO in order to. It deliver more exceptional customer experiences and improve our retention right through better data management, so you can. Identify is that is that one. The key kind of the the the key outcomes here and then the next step would be to understand what what environment are you operating in. Yes, you want to improve your customer attention. Your customer experiences, but what is your? What is your overall operating environment here, right? How willing is marketing? Are marketing and sales going to be to work? With you as the CEO. How do they? How does marketing and sales operate are? Are they relatively autonomous? Do they have a lot of freedom in order to manage customer relationships, or is that more of a collaborative enterprise within the environment, right? So understanding the environment, you’re going to be operating in from kind of a culture perspective. Who thinks they own the customer? When you embark on this, you’re going to hear that word often. Well, we own the customer, we’re finance, and we own the customer sales owns the customer or account services, owns the customer who thinks they own the customer today. Is there a belief that one group owns them or is it more of a again a collaborative thing this? Will start to give you some. Insights into the overall operating the model that you that you’re working with. Then sit down and have conversations with those people. What does owning customer data mean to you as VP of Marketing or to you as VP of Sales? You’ll start to understand how hard maybe are some of the kind of the the the lines between silos. The lines between operating groups right? Is there a highly collaborative environment there? Or is there more of a friction? Type environment where where people don’t really like to share data and and maybe sales is a bit of a distrust of marketing and vice versa. Maybe the product organization thinks the sales and marketing are are not not operating that well and maybe product thinks they own the customer. It’s those types of things you want to. Kind of get. A feel for. Right in terms of what is the operating model? What’s the overall culture when it comes to this data? This one key outcome by the way, by the way, a key to this whole thing being MVP driven here is to focus on a limited number of outcomes. I should discuss that. Early on in step number one, when defining what your outcomes. Going to be. Limited number of outcomes. Not all of them. One or two right? If you want to take an MVP MVP approach here to a strategy and I would argue that is the best thing that you can do to start showing some quick wins is to start showing some value and not get stuck in an 18 month long discovery and consulting. We are trying to figure out how to address all of those key dependencies that we talked about earlier. Instead, focus on one or two key out. Improving customer retention is a great example. Lowering your supply costs is a great example. Optimizing your supplier relationships, consistent terms of pricing with things you’re buying from your suppliers on and on. A KPI I’m talking about a specific business outcome where you will have KPIs that are tied to customer retention. Not very many right, maybe 1/2 a dozen. That could be. Drive to customer retention right, but be limited in your focus of what outcomes. You want so the. Whole key to this model guys. The whole key to being kind of agile capital a taking more of an MVP approach here is to say I’m not going to solve for everything from a data strategy perspective. I’m not in time when we look at this model. There’s a reason why it’s a wheel here. This wheel is going to spin, so you will deliver, right? You’ll show some value and then you’ll do it again and then you’ll do it again and then you’ll do it again. And over time you will address every aspect of your data strategy. You’ll over time you will, but in the short term, take a very limited. Very focused approach on a limited set of outcomes. I would argue one, maybe two at the most at the. But getting back to those conversations around kind of data culture, figuring out what what, where, where you’re operating, what’s the environment that you’re walking into and knowing what are some of those kind of those hard boundaries you think you’re going to hit, right? What are some of the hard boundaries are within sales within marketing? Within these these organizations, where are people going to be willing to work with you, and where are they going? To be willing to work with you. Because of cultural constraints because of constraints within the operating model. Same is true and we work. Around to the next to the next kind of stop on this model, which is data and analytics, governance, maturity. Right, you are going to find that you have. You have probably probably some gaps to fill from an overall data analytics governance maturity, right? Do you need to? Go and hire some expensive consultants to do a maturity assessment. Well, probably not, probably. Not for this goal around right? For for, for, for future goal. Rounds and and when you want to address things on. A more of an enterprise wide perspective. Perhaps, but I think you. Will quickly find. Right, if if you go into this and you’ve. Got one or two or three. Analysts that you can work with. If you’ve got a team of people that you can work with to hold these interviews, and to have these conversations right, I. Think you’re going? To find rather quickly where you stand from a data and analytics governance perspective from a maturity perspective. Right, you can go hire some consultants to do a maturity assessment if you want. Chances are what they’re going to come back with is out of a scale. Of five, you come back at a 2 or 2.5. I just I. Saw that over and over and over and over again. The results are almost always the same and what they almost always say for new CDO’s. Is that yeah, the data? Your data data tends to be highly siloed. You take a bit of a firefighting or reactionary approach to data management. You’ve got some data quality issues. It is not really being used as a leveraged as an asset from an analytical perspective, you’ve got some distrust with your report. You may have some reports that are being produced in a regularly. You’ve got some dashboarding, but often it’s highly siloed within individual departments or operating units. You lack some enterprise wide views and the the the symptoms of a level 2 maturity. Here are are common, right? And they’re easily identified based on some of the things that I just. Shared with you and and and other maturity models that are. Widely available online. Do you need to go and hire Deloitte to go apply their their their? Maturity model well. Maybe in time, but I would say if you want to be MVP and if you want to be quick and you want to show quick wins, you could probably have three or four or five days worth of interviews with key stakeholders and understand pretty quickly where you are and chances are everything I just described. Describes where you are highly solid, highly reactionary, lack of an enterprise wide data strategy, lack of an enterprise wide governance model, lack of enterprise wide MDM. On and on. The the The what I saw here as a. Gartner analyst was almost consistent. It was always that way so. Again, these kind of things from the outer ring of this model when it comes to your overall business strategy when it comes to your culture and your operating model, when it comes to your overall governance maturity. You are not going to change these things in the short term. These are constraints and you need to figure out how to operate within those constraints in terms of delivering value quickly to your organization. So do you need to fix them in the long term? Probably probably yes, right? You you certainly need to up your game. From a data analytics governance perspective, you probably need to address some of these issues related to your culture in your operating. But are you going to make that a hard dependency in order to deliver value? No, you need to find a way to deliver value within those constraints. If you want to extend your tender tenure if. You want to. Avoid the situation where in 12 to 18 months you’re being evaluated in around. You know some sort of inability to deliver value. If you want to be. API. Would argue I would stress to take take. Those things in. The outer ring of this model, as as. As constraints and find ways to work around them. Right, a great example here. A great example is leveraging more analytical insights instead of operational insights and what I mean by that. Is you could. You could identify pretty quickly. Let’s get back to the customer experience model. Here you can identify where the customer experience deliverable. You can identify pretty quickly that the way that you onboard. Customers in the way that you manage customer data is probably likely pretty broken. I’m almost always is right where you’ve. Got sales people. Doing some silly shenanigans in in your C. Program and where there’s no integration between your CRM and between your ERP or or whatever systems that you use to make things or deliver things. Or or or. Recognize revenue that there’s a break between CRM and downstream ERP processes. Almost almost always happens. You can identify that you’ve got some broken business processes right. Chances are you do. Right are you going to say OK as a way to solve for better customer experience? I need to change how the business operates. I need to change how we capture customer data in our CRM. I need to put more constraints around how salespeople enter data into the CRM because they need to stop doing stupid stuff when they enter new accounts. All that stuff may be true. It may be true, but addressing. Any issues related? To you know your your existing operating model, how you manage customer today those are not going to be short term fixes. They’re just not. You’re going to hit friction, you’re. Going to hit pushback. You’re going to hit people in in sales saying, if you make my sales people do this, it’s going to slow. Down our ability to close new deals. And the minute that’s said, and then the minute that happens, you’re dead in the water. You’re not going to change that operational process. You can keep trying. You can keep trying to kind of pound that round peg into the square hole, but it’s not going to happen in the short term. It’s just not. So a way to work around that. Just to focus more on analytical insights, are there things that you can do from a governance perspective, or at least from an analytical perspective to at least show and highlight how managing customer data better will deliver on an exceptional customer experience and will deliver on retention? I’ll give you an example. Could you use some improved analytics? Maybe a little bit of MDM and maybe a little bit of governance? Not a ton, but take take a light handed approach to those things to deliver a customer 360 they could show where customers are traversing your lines of business or could show how you’ve got them. Same customer record five or six times in your in your support system and your customers in your in your kind of your the system you use to manage trouble tickets or or or any sort of customer. Support issues could you show? So where you have multiple customers showing up and maybe instead of seeing 5 records for Acme Incorporated your customer support, people could actually just see one and all you’ve done here is to aggregate data and display it a little differently. You haven’t changed how customers are onboarded. You haven’t. Changed how sales people. Put new new accounts into your CRM. You haven’t changed. Any of that stuff you’ve just created a view using some basic governance rules related to how do we define customers? Some basic data quality rules about you know how do we normalize the data and maybe even merge some records together if that’s an. Option of some some basic integration, some some basic, maybe MDM and where you’ve created a 360 view now did you fix all the data? I would say no, don’t do that. Don’t put a data quality cleanup in the critical path of what I was just talking about, because that’s going to. Take a long time, right? Can you instead deliver on that outcome that we were talking about better customer retention, right? Working with the data that you’ve got? Can a 70% of the solution or an 80% of solution still deliver on that outcome and still deliver value to the organization? I would argue it can. But again, I used to. Hear all the. As a Gartner analyst, well, OK, even to do a customer 360 to do a really accurate robust customer 360 I need to. Fix all the data. Well, good luck with that one. The data is never fixed fully right? Two for most larger organizations, once you start talking about 20 thirty 40,000 customer records, particularly B2C. But even B2B456 thousand records cleaning all that stuff up. You’re talking about hiring a small army. And chances are you’re talking. About months and months and months and. Months and by the. Time you send. A ship you’re likely back to where you started from anywhere. Is that data cleanup really? Going to be part of your MVP in order to deliver value here, no, I would say it’s not I, I would say you need to work instead to set expectations with the business that you’re going to get 70% of the. Solution not 100%. Of the solution. But if you’re focused on retention, if you’re focused on KPI’s, if you’re. Focused on outcomes. What you can do? Is the the phrase I used to. Use is you can price. In some of that inaccurate data meaning create an expectation with the business that you will improve customer retention 4% instead of five or six or seven. Know what your marker is. Know what you’re aiming for. Where if you understand the data is probably pretty bad. If you understand your maturity levels are low and it will take some time to fix all that other stuff, like, you know shenanigans going on in sales or fixing low poor data quality or poor data integration. All those other things take time to fix that, but can you still deliver some benefit without getting into these giant galactic prolonged data cleanups? These prolonged initiatives that are. Take forever and ever to deliver. Against, I would argue you can, I would. Argue that you. Shouldn’t fall down into this trap of thinking that you have to clean up all your data and fix for all of these things on this model cause you to. Well, you don’t. That’s what being. Agile is all about how do you deliver. Value in the case of this. Model that I’m sharing with you. How do you deliver value within the? Constraints that you’re dealing. With particularly from a government perspective from a kind of a operating model perspective, from a culture perspective. The middle of this ring is really where the rubber hits the road. It’s executing right? And and we could have an interesting conversation about. Well, strategy isn’t execution and and and. And I know this is a little bit of. A twist in this model here, but what I would argue. Is that to go from an MVP strategy to this this kind of repeated prolonged programmatic focus on strategy because strategy? Is not a one. And done, it’s a program, it’s a. It’s a living thing that should be consistently revisited. I would argue to go from an MVP phase one limited scope. Approach to a broader kind of programmatic approach. That you do need to do. Deliver because the more that you deliver and the. More value you show. The more your governance maturity will grow. The more your operating model will likely can change right? The more your stakeholders in marketing, sales, finance, logistics will want. To work with you. Because they’ll have seen the value that you have provided. In the past, so instead of having a conversation of, I don’t want to work with you. I don’t want to do this, don’t make me change, don’t make me change how we onboard customers or onboard suppliers and manage any of our processes. You’ll go from that to. Well, I heard I played golf last week with our Chief Revenue Officer and I heard that you delivered some incredible stuff from a retention perspective, you enabled cross selling and upselling and we and our revenue number jumped up. I I didn’t know we could even do that through better data management. How can I work with you again? How can I work with you? CDO I want to. I want to do this. In in my world, in my procurement world, or whatever world that is right. So I would argue here that if you want to succeed as a CEO, if you want to succeed at a data strategy. If you want the data strategy to be. An evolution if you and and and it necessarily is. It will need to be. I would argue that you do need to incorporate some idea of executing against the strategy as a part of your strategic model where you plan to deliver iteratively where you plan to deliver in small bite sized chunks as a part of executing on that strategy where the strategy. Continually evolves based on your ability to deliver. That’s the middle of. This ring. This starts to get into more kind of classic data operating model type stuff right where you start over on the right hand side where you need to have defined success metrics, right? You need to go from a high level metric of better customer attention to what are the actual KPIs needed to do that. What are the five or six or seven KPIs we use to measure retention? There’s probably a retention measure metric. There’s probably you know renewal rates. There’s probably average, you know, selling price on renewal, whatever those metrics are, chances are. Probably got some metrics to measure retention or whatever your out. Myth moving along the model here you do need to have some sort of gap analysis. You do need to have some sort of road map. You need to know where where all these things fit together, right? So you need to have a high level understanding of what some of the desired outcomes here are as a part of that outer ring, start high level, have conversations with sea level peers. Have conversations with other executive management, understand what their key priorities are. Write all those down. They’ll probably put together 15. Or 20 of them. Right, so you’ll have an idea of what that high level road map will need to look like. This is this is this is like phase 5101520 in this whole MVP approach. So as a part of that authority, as a part of that discovery process, you do need to have some idea of relatively high level of what your business stakeholders really want from you that needs to go on or a road map, but again. Focus on one thing and one thing only when you’re well one or two things trying to execute and be more MVP. When it comes to this. Your government model. You need to understand what that government model is going to be. Will you be highly centralized? Would be highly how they decentralized right? Who’s going to own data? Even though I kind? Of really despise that phrase? Because when it comes to data, particularly master data, it’s it’s its own collaboratively. The idea that any one person could own a customer record, I think is is a little bit of a misnomer. But understand what the governance model is going to be, what approach to governance you’re going to take? Who’s going to chair your governance committees at an enterprise wide level and at an operating level? Like this is where things like a governance framework come into play and there are lots of governance frameworks out there, but having some idea of your governance framework is going to be important. Now, if you had to solve for everything meaning. If you had to. Solve for every one of those 15 or 20 outcomes that I was talking about just now. If you had to solve for all of those, your government framework here would be huge. Right, and figuring this out as a dependency to deliver on your strategy? Again, that’s high risk, right? If you look at. Governance and any governance framework model. I’m not sharing that with you. Now that could be a separate podcast, but just Google data governance framework. There’s a lot of them out there, they’re all pretty good. We had a good one at Gartner. You’ll find a lot of key dependencies that go into governance. Network retention, archival data access, security, even ethics for heavens. Part of is part of the data governance framework, so the reason. Why we want to be MVP? Focused Razor focused on one outcome at a time. At the beginning is because when you’re focused on one outcome, better customer retention, the governance dependencies, there will be limited. You won’t need to figure out. Every business rule for every policy for every aspect of the governance framework, for every nugget. Of data in your org. Overtime as this wheel spins you’ll get there, but for now you just need to figure out the governance needed to enable better customer retention. Simple stay focused. Keep a limited scope. Be agile, deliver on one outcome, figure out the governance dependency for that one outcome instead of figuring out the governance dependencies for everything. Because if you try to figure out the government dependencies for everything, you’re going to be at it every. Day for the next three years. Two to three years. Easily right? And that will consume every resource you’ve got. You won’t have delivered value, and it’s not going to be good. It’s not your organization. What’s the organization here? What what organization is needed in order to deliver against these short term priorities? I would argue that most of the positions. Within your data, your. Data and analytics organization within your CDO office. To deliver on one of those key outcomes, a lot of those key roles responsibilities are are are are going to be as a part of that initial deliverable. You’ll you’ll have business analysts. You’ll have some sort of BI expert. You probably have some sort of data architect. You probably have some sort of overall program lead. You can identify pretty quickly what are the key roles needed in order to deliver against that. One outcome and again as you do this over and over and over, the team will expand. Right the the people will expand. You will need to adjust. But I would be, I would argue that even for. That phase one. Deliverable, you have a pretty good foundation from an organization perspective. Separate podcasts. We can talk about roles and responsibilities of I’ve I’ve consulted to literally hundreds of companies on. How to do this? Technology, the last little bit here. Never lead with technology. Technology should always be towards the end of your your your strategy definition. What are the tools and technologies needed to support everything else? We were just? Talking about in this case, taking an MVP approach, what are the tools and technologies that are enabled? That are required to enable better customer. Now I can. Hear a lot of you out there saying. Well, wait a minute here if we just focus on this and have this MVP approach from an IT perspective, we’ll then how do we make sure that we’re buying tools that are scalable? How do we make sure that we avoid not buying the same tool over and over and over again? And this MVP approach doesn’t really work from a long term strategy perspective when it comes to your overall architecture. Some of the concerns there are certainly valid, so you need to. You need to find a balance here. That outer ring and that phase one that I was talking about where you were sitting down with your fellow peers and you’re talking to senior executives about what they want and putting together everybody’s wish list, right? If you’ve got an idea of that high level wish list. Of all the things that your stakeholders want through better data through better governance, if you got an idea what that wish list is for an architect who is worth his or her. Salt I would. Argue that you could have a pretty decent understanding at a high level. At a high level of what the overall technology architecture should look like, if you looked at all 15 or 20 of those wish list items, I think pretty quickly you’d have a decent understanding of what you needed from a high level systems perspective. If you knew what some of your constraints were existing today from a from from an operating model perspective and overall corporate. Culture perspective some of the constraints related to your governance maturity. If you understood all of those things, you put them together. I would argue if you had a pretty talented architect, you could find a way to balance. Short term, the short term architecture needed to deliver on this MVP versus some of the tension that may exist with the longer term architecture you will consistently hear IT architects saying, well wait a minute. We can’t be shortsighted. We need an architecture that is scalable, flexible, that will grow the business. Those things are absolutely accurate. They are absolutely accurate, but too much of a focus on that could negate your ability to deliver in the short term, right? Do you need to go and buy a massive data governance solution? A a enterprise class MDM, an enterprise class data quality tool to do all the things that we were just talking. An example again with the customer retention or maybe a. Customer 360 Do you need to go buy all of? Those tools to deliver on that. Probably not. Probably not. Are those the right tools to have longer term from an enterprise wide perspective from a long term perspective of where you want to go with this road map? Yeah, probably they probably are given the size of your company. I mean it it it’s impossible to know, but you get my point right. There’s going to be a bit of a balance and a little bit of attention. Here, maybe as a phase one. All the tool you need is something like a customer data platform, a CDP you can go subscribe to that, go buy one for a year. 203040 grand is it going to be kind of enterprise class MDM? No. Is it enterprise class data quality? No. Can it help you deliver 6070% of a 360 when it comes to customer data? This. Is just one example by the way guys. Maybe it can, and maybe that’s OK as a short term solution to show the value here. So my point is, is that if you hire an architect as a part of that team as a part of that and as CEO office, you want that architecture to understand hey where we want. Where we going here? Where do we think we need to be based on our wish? List of items based on all of our other constraints based on on where we want to be longer term. What the architecture look like for that? And what does the architecture look like for right now? And what’s the happy balance there right? Can we go and and subscribe to the CDP without negatively impacting our ability to be flexible and to be extensible and configurable and and and and have an architecture? The growth of the business? Maybe you can’t. Maybe you can’t. Or maybe you can’t. It also depends on the existing architectures that. You’ve got, so again, it’s all about a balance here. But technology never solved anything on its own. People process technology. It’s never a silver bullet. What you’re going for here is an understanding of how do I deliver value? How do I deliver value? What’s the fastest way to quick to to do that right within the constraints that I’m operating in so that we can turn around? And do it again. And then do it again and then do it again and. I would argue if you. Do this for a. Year if you find a way to iterate and deliver value against 456 high level outcomes. If you can deliver some value from a customer data perspective or supplier data or whatever, whatever the key things are, that really, really matter to your organization based on input from your, your, your, YOUR peers in the East suite if you can. If you can provide value, move the needle half a dozen times over the next year, maybe three or four times over the next year, you’re. Going to be in a far. Far better position to leverage those successes. To get additional funding. To take maybe a deeper look at some of the issues that we talked about before, maybe to go and do a deeper level maturity assessment, maybe to go into and and and to get some consultants to help really focus on that longer term road map that we were talking about. Maybe you do. Bring some consultants in to help you address some. Of the cultural operating model. But if you’ve been doing this for a. Year and you’ve been showing value. And you’ve got your CEO is ready to reap for the next year. You’re getting increased budget. You’re getting increased visibility. You’re getting increased traction, you’re. Getting more of your partners. Saying to you, I want. To work with you right? Keep doing that that. Will earn you the right to start working on some of these really longer term things. Like addressing some of these kind of operating model challenges, culture related challenges or maturity level challenges on the outside of this ring. That’s when you can start. Doing a little bit of both. Right where you can keep working in MVP fashion, keep delivering value in small chunks, but then start focusing on some of the bigger, more intractable stuff that the the two to three-year long stuff that that you do need to address ultimately. But having the balance between the two instead of at the beginning saying hey, I’m just going to be focusing on this long term stuff that I probably don’t have a lot. Of ability to influence in the short term. That is my MVP data strategy. If I was hired as a CEO tomorrow, that’s an approach that I would be taking in order to make sure that I was delivering value in the short term and not getting too hung up on things that I really can’t change. The things that I really don’t have a ton of control over, at least in the short term. The best way to get control. Over those things like operating model. Cultural issues and on and on is to show. Value and to. Show to your peers. That union business and that you are able to deliver the value which. Will earn you the right. To start having conversations about fixing operating models and fixing corporate culture so. That’s really the high level discussion point for today. I hope you found some value in this. I I hope you found the kind of the approach. Here with just. Yours truly. Talking about data. A little bit different looking forward. To the next episode of CDO Matters. This was our 14th. I think. It’s just kind of cool. We’ve we’ve got more coming. Every two weeks we have more and more of. These coming we’ll. Most certainly having interviews with with more CDO’s other kind of movers and shakers in the space. My privilege to bring this content to you. I hope you found some value in our conversation, or at least my conversation today. We’ll look forward to seeing you on another episode of CDO Matters sometime soon. 


How can today’s Chief Data Officers help their organizations become more data-driven? Join former Gartner analyst Malcolm Hawker as he interviews thought leaders on all things data management – ranging from data fabrics to blockchain and more — and learns why they matter to today’s CDOs. If you want to dig deep into the CDO Matters that are top-of-mind for today’s modern data leaders, this show is for you.

Malcolm Hawker
Malcolm Hawker is an experienced thought leader in data management and governance and has consulted on thousands of software implementations in his years as a Gartner analyst, architect at Dun & Bradstreet and more. Now as an evangelist for helping companies become truly data-driven, he’s here to help CDOs understand how data can be a competitive advantage.


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